Storylane MCP Server for Pydantic AIGive Pydantic AI instant access to 12 tools to Create Demo Link, Get Demo, Get Demo Analytics, and more
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Storylane through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
Ask AI about this App Connector for Pydantic AI
The Storylane app connector for Pydantic AI is a standout in the Marketing Automation category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
agent = Agent(
model="openai:gpt-4o",
mcp_servers=[server],
system_prompt=(
"You are an assistant with access to Storylane "
"(12 tools)."
),
)
result = await agent.run(
"What tools are available in Storylane?"
)
print(result.data)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Storylane MCP Server
The Storylane MCP server connects your AI agent directly to your demo infrastructure. Query demo completion rates, create personalized demo links for prospects, and sync engagement data natively.
Pydantic AI validates every Storylane tool response against typed schemas, catching data inconsistencies at build time. Connect 12 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.
The Storylane MCP Server exposes 12 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 12 Storylane tools available for Pydantic AI
When Pydantic AI connects to Storylane through Vinkius, your AI agent gets direct access to every tool listed below — spanning product-demos, interactive-content, lead-engagement, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Generate a new trackable demo link
Get metadata and status for a specific demo
Get engagement metrics for a specific demo
Get information about the current authenticated user
Get detailed information for a specific viewer session
Retrieve metadata about the current Storylane workspace
Retrieve all active links associated with a specific demo
List all published demos in the workspace
List granular session analytics for demo viewers
List teams within the workspace
List all users and their roles in the workspace
Update settings for an existing demo link
Connect Storylane to Pydantic AI via MCP
Follow these steps to wire Storylane into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install Pydantic AI
pip install pydantic-aiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use Pydantic AI with the Storylane MCP Server
Pydantic AI provides unique advantages when paired with Storylane through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Storylane integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Storylane connection logic from agent behavior for testable, maintainable code
Storylane + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Storylane MCP Server delivers measurable value.
Type-safe data pipelines: query Storylane with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Storylane tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Storylane and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Storylane responses and write comprehensive agent tests
Example Prompts for Storylane in Pydantic AI
Ready-to-use prompts you can give your Pydantic AI agent to start working with Storylane immediately.
"List all our active product demos."
"Create a personalized link for 'Analytics Deep Dive' for Acme Corp."
"Show the completion rate for the 'Platform Overview' demo."
Troubleshooting Storylane MCP Server with Pydantic AI
Common issues when connecting Storylane to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiStorylane + Pydantic AI FAQ
Common questions about integrating Storylane MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.